In an industry where the demand for rapid digital innovation often clashes with the complexities of legacy infrastructure, global software leader BMC has unveiled a significant series of AI-driven advancements for its Control-M and BMC AMI product portfolios. Announced on January 26, 2026, these innovations are engineered to dismantle long-standing barriers between technical IT functions and business objectives, particularly within the realms of mainframe operations and complex workflow orchestration. By embedding generative AI and intelligent automation directly into its core solutions, the company aims to empower a broader range of users, streamline issue resolution, and transform vast repositories of institutional knowledge into accessible, actionable insights. This strategic infusion of artificial intelligence is set to modernize enterprise systems, making them more responsive, resilient, and aligned with the fast-paced demands of modern digital business.
Revolutionizing Workflow Orchestration with Generative AI
A central pillar of the recent announcement is the introduction of a groundbreaking generative AI feature within the Control-M workflow orchestration platform, designed to democratize the creation and management of complex business processes. This innovation allows users, particularly those with deep business knowledge but limited technical expertise, to construct sophisticated workflows using simple, natural language commands. By translating conversational requests into executable automation, the feature effectively removes the traditional barriers of coding and scripting, empowering a new class of citizen automators. This shift not only accelerates the development and deployment of critical workflows but also ensures that the automation being built is more closely aligned with business needs. The ability for a business analyst to articulate a desired outcome and have the system generate the corresponding workflow represents a significant leap forward in making automation more intuitive, accessible, and responsive to the dynamic requirements of the enterprise.
Further enhancing its automation capabilities, Control-M has significantly broadened its integration ecosystem to include leading AI platforms such as AWS Bedrock, Google Vertex AI, and Crew AI. This expansion enables practitioners to orchestrate multiple, specialized AI agents to collaboratively execute highly complex, AI-centric tasks, thereby accelerating innovation and helping organizations scale their artificial intelligence initiatives more effectively. Complementing this is the launch of the Control-M Event Driven Workflows capability, a feature that directly addresses the growing necessity for real-time responsiveness in modern, event-driven architectures. By actively listening for signals and triggers from critical event-streaming platforms like Kafka, Amazon SQS, and RabbitMQ, Control-M can now automatically initiate, adjust, or adapt workflows on the fly. This capability ensures that business processes react instantaneously to real-world events, from supply chain disruptions to customer interactions, fostering a more agile and intelligent operational environment.
Infusing Mainframe Operations with Intelligent Assistance
For the mainframe, which remains the backbone of many large enterprises, the updates center on the BMC AMI portfolio, highlighted by the introduction of the BMC AMI Assistant. A key component of this initiative is the Knowledge Expert Chat, an AI-driven guidance tool embedded directly into nine different BMC AMI development and operations solutions. Available at no additional cost to licensed customers, this feature provides clear, natural-language answers to complex technical queries by drawing from BMC’s extensive knowledge base of documentation and deep domain expertise. This integration allows development and operations teams to resolve issues more rapidly, reduce their dependence on a shrinking pool of seasoned mainframe specialists, and ultimately improve system performance and service reliability. By bringing expert knowledge directly into the user’s workflow, the tool eliminates the need for context switching and lengthy searches, enabling teams to maintain operational excellence with greater efficiency.
Addressing the widening skills gap in mainframe talent, BMC is also introducing the Knowledge Hub capability, which is currently in a managed beta phase. This feature is designed to capture, centralize, and surface an organization’s scattered institutional knowledge, making decades of experience and best practices readily available through intuitive, AI-powered interactions. Furthermore, the new BMC AMI zAdviser Development Team Analysis provides a powerful AI-driven tool for development leaders. It consolidates a wide array of DevOps telemetry—including activity metrics, productivity data, and failure patterns—into a unified narrative report for each application. This comprehensive analysis helps leaders make more informed decisions by quickly identifying application stability risks, uncovering knowledge concentration within teams, prioritizing areas for improvement, and reducing overall operational exposure. By providing deep, data-backed insights, this tool empowers organizations to proactively manage their mainframe application lifecycle.
A Strategic Step Toward an Autonomous Digital Enterprise
The series of AI-powered innovations launched by BMC represented a decisive move to integrate deep intelligence into the core of enterprise IT. By leveraging AI to unlock value from data and drive business insights, these enhancements provided customers with the tools needed to build a more resilient and advanced mainframe environment capable of supporting ambitious digital transformation efforts. The introduction of natural language workflow creation in Control-M and the embedded expertise within the BMC AMI portfolio signaled a clear direction toward simplifying complexity and empowering teams across the organization. These developments were not merely incremental updates; they constituted a foundational shift aimed at transforming legacy systems from operational necessities into strategic assets, ensuring they could meet the dynamic, real-time demands of the modern digital landscape.
